DocumentCode
3355177
Title
Edge-aware intra prediction for depth-map coding
Author
Shen, Godwin ; Kim, Woo-Shik ; Ortega, Antonio ; Lee, Jaejoon ; Wey, Hocheon
Author_Institution
Signal & Image Process. Inst., Univ. of Southern California, Los Angeles, CA, USA
fYear
2010
fDate
26-29 Sept. 2010
Firstpage
3393
Lastpage
3396
Abstract
This work proposes a new intra prediction coding scheme for depth map images used in view interpolation. The main goal is to design a prediction scheme which can reduce the prediction error energy in blocks with arbitrary edge shapes. This will reduce the rate needed to encode such blocks while also eliminating some of the annoying artifacts caused by quantization. Since depth maps typically consist of smooth regions separated by edges, we find it sufficient to design prediction schemes which can make effective use of edge information. Working from the intra prediction framework in H.264, we provide a graph representation of pixels in a block and pixels from previously coded blocks and construct an edge-aware prediction scheme based on this. We also employ existing rate-distortion (RD) optimization methods to further improve the coding performance. Our proposed methods reduce the bit rate for depth maps by up to 29% for a fixed interpolated PSNR for some sequences.
Keywords
edge detection; graph theory; image sequences; interpolation; prediction theory; rate distortion theory; video coding; H.264 prediction framework; RD optimization; arbitrary edge shapes; depth-map image coding scheme; edge-aware intra prediction; error energy prediction reduction; fixed interpolated PSNR; graph representation; quantization; rate-distortion optimization methods; view interpolation; Bit rate; Encoding; Image edge detection; Interpolation; PSNR; Pixel; Shape; Multiview plus depth (MVD); depth coding; rate-distortion optimization; view synthesis;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location
Hong Kong
ISSN
1522-4880
Print_ISBN
978-1-4244-7992-4
Electronic_ISBN
1522-4880
Type
conf
DOI
10.1109/ICIP.2010.5652792
Filename
5652792
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